Combined Prediction Algorithm for Coal Gas Emission Amount

Abstract

With the continuous development of data mining technology and machine learning, artificial intelligence has been applied to various industries, and good results have been made in a combined prediction algorithm for coal gas emission. The detection of coal gas concentration is not only related to production safety, but also has a very important impact on the economic development of the country, The gas explosion has a great effect on the life of the national and the safety of the property. In this paper, the exponential smoothing algorithm, gray prediction algorithm and phase space reconstruction principle are improved to form a new combined model algorithm, which is used to predict the gas quantity of a coal mine. It is verified that the accuracy is 98.21%. You can apply a composite model to a Abnormal analysis of gas concentration in mine, risk prediction of gas accident, etc. The coal mine gas accident is predicted in advance to reduce the risk.